The toolkit for multivariate data analysis: TMVA 4

The toolkit for multivariate analysis, TMVA, provides a large set of advanced multivariate analysis techniques for signal/background classification. In addition, TMVA now also contains regression analysis, all embedded in a framework capable of handling the preprocessing of the data and the evaluati...

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Detalles Bibliográficos
Autores principales: Speckmayer, P, Hocker, A, Stelzer, J, Voss, H
Lenguaje:eng
Publicado: 2010
Materias:
Computing and Computers
Acceso en línea:https://dx.doi.org/10.1088/1742-6596/219/3/032057
http://cds.cern.ch/record/1270192
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author Speckmayer, P
Hocker, A
Stelzer, J
Voss, H
author_facet Speckmayer, P
Hocker, A
Stelzer, J
Voss, H
author_sort Speckmayer, P
collection CERN
description The toolkit for multivariate analysis, TMVA, provides a large set of advanced multivariate analysis techniques for signal/background classification. In addition, TMVA now also contains regression analysis, all embedded in a framework capable of handling the preprocessing of the data and the evaluation of the output, thus allowing a simple and convenient use of multivariate techniques. The analysis techniques implemented in TMVA can be invoked easily and the direct comparison of their performance allows the user to choose the most appropriate for a particular data analysis. This article gives an overview of the TMVA package and presents recently developed features.
id cern-1270192
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2010
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spelling cern-12701922022-08-17T13:24:44Zdoi:10.1088/1742-6596/219/3/032057http://cds.cern.ch/record/1270192engSpeckmayer, PHocker, AStelzer, JVoss, HThe toolkit for multivariate data analysis: TMVA 4Computing and ComputersThe toolkit for multivariate analysis, TMVA, provides a large set of advanced multivariate analysis techniques for signal/background classification. In addition, TMVA now also contains regression analysis, all embedded in a framework capable of handling the preprocessing of the data and the evaluation of the output, thus allowing a simple and convenient use of multivariate techniques. The analysis techniques implemented in TMVA can be invoked easily and the direct comparison of their performance allows the user to choose the most appropriate for a particular data analysis. This article gives an overview of the TMVA package and presents recently developed features.oai:cds.cern.ch:12701922010
spellingShingle Computing and Computers
Speckmayer, P
Hocker, A
Stelzer, J
Voss, H
The toolkit for multivariate data analysis: TMVA 4
title The toolkit for multivariate data analysis: TMVA 4
title_full The toolkit for multivariate data analysis: TMVA 4
title_fullStr The toolkit for multivariate data analysis: TMVA 4
title_full_unstemmed The toolkit for multivariate data analysis: TMVA 4
title_short The toolkit for multivariate data analysis: TMVA 4
title_sort toolkit for multivariate data analysis: tmva 4
topic Computing and Computers
url https://dx.doi.org/10.1088/1742-6596/219/3/032057
http://cds.cern.ch/record/1270192
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